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Enhance knowledge for more informed decisions

Find hidden information in your dark data

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Dark data discovery leveraging
biomimetics for innovation

Real-World Data Sources
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Digital Twins
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Knowledge Graphs
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Because data-driven decisions matter now more than ever

  • Unleash the power of enterprise-wide discovery and innovation
  • Quickly determine cause and effect for superior decision support
  • Test scenarios with digital twins and determine best outcomes

Enable fast, confident decisions across the enterprise

  • Reliable Analytics for unbiased discovery
  • Arm decision-makers with trustworthy information
  • Faster insights create actionable intelligence

Technology

Our flagship AI solution, Causaition™, employs biomimetics and proprietary human-based cognitive modeling to reveal causality and complex realities.

Causaition employs an advanced digital twin ecosystem combined with a multi-disciplinary approach that follows a set of principles rather than deterministic code when solving problems.

Causaition’s dark data discovery generates new insights enhancing business efficiencies through dynamic unbiased exploration of options and tradeoffs with evidence traceability.

Causaility has partnered with RYLTI/RYAILITI and other innovators in biopharma, laboratory services, genomics, energy, communications, and financial services to offer a range of solutions built on the leading AI platforms.

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News Archive
Advancing Genomic Medicine and Informatics
June 24, 2024
Applied artificial intelligence, particularly large language models, in biomedical research is accelerating, but effective discovery…
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News Archive
First Study Using Biomimetic Digital Twins Published
May 17, 2024
Biomimetic digital twins are about to revolutionize the fight against endometrial disorders, blending genomics and…
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News ArchiveJune 24, 2024
Advancing Genomic Medicine and Informatics
News ArchiveMay 17, 2024
First Study Using Biomimetic Digital Twins Published
News ArchiveApril 17, 2024
Researchers Present First Study Using Biomimetic AI Digital Twins
BlogNovember 14, 2024
Defining the Problem – Getting Started with Causaility
BlogOctober 25, 2024
Dark Data Analytics
BlogSeptember 27, 2024
Part 6: Large Language Models have Roadblocks to Discovery

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Real-World Data Sources

Real-world data sources are the multiplicity of available databases ranging from siloed enterprise to public and private records. This information is collected and input to the Causaition™ AI platform with its data lake implementation that eliminates system integration complexities. Small/Wide data methods connect diverse and dynamic information from disparate data silos.

This wealth of data allows companies to refocus on a number of key change drivers, such as accelerating the pace of scientific innovation, addressing rising development costs, to understand consumer credit card spending, geospatial data, and web-harvested data (as used appropriately and adhering to privacy standards). Real-world data allows researchers to intensify their focus on “what if” scenarios. The advanced analytic capabilities of the Causaition platform optimizes results delivering a high level of confidence — for example, unbiased analytics to fuel research decisions, support market access, or sharpen product plans. 

Digital Twins

The Causaition™ AI platform is based on a digital twins architecture delivering: RWD + RWR = RWE (real-world data + real-world reasoning = real-world evidence). A digital twin predicts how conditions change over time. Put simply, it is a virtual replica of a physical object or system that can be used to simulate behavior to better understand how it works in real life. Digital twins are linked to real data sources stored in the Causaition cloud. We use biomimetic knowledge engineering to build and update our digital twins to investigate solutions from modeling dynamic evidence driven interactions of relevant change drivers. Real-time twin updates are consistent with and reflective of the original data set.

When interconnected within a Causation platform, the digital twins can form what’s known as an enterprise metaverse: an immersive digital environment that replicates and connects every aspect of an organization to optimize simulations, scenario planning, and decision making.

Knowledge Graphs

Causaility’s AI platform, Causaition™, employs advanced knowledge graphs to deliver groundbreaking actionable insights making the innovation and discovery process faster, better, and less expensive while, at the same time, increasing efficiencies and mitigating bias. Within a knowledge graph is the knowledge model which is a collection of interlinked descriptions of concepts, entities, relationships and events. In the Causaition platform, the model content is integrated and rationalized by a combination of:

  • Automated and manual processes
  • Standard and proprietary methods
  • Subject Matter Expert (SME) input

This real-world reasoning approach enables the construction of models that integrate highly diverse elements and information sources for exploration and discovery. Filter out potential misinformation by modeling the abstract context and using that model to compute the relevance of the available data points, providing a framework for data integration, unification, analytics, and sharing.